dse is a simple and crude way of not executing SQL queries in sequence, but caching values until a given max value has been met and then execute them using the executemany-method. The result can be huge speed gains.
dse was only tested on SQLite3 but intended for use in django as well.
Example usage:
import sqlite3 # for testing purposes
from dse import DelayedSqlExecutor
conn = sqlite3.connect(':memory:')
cursor = conn.cursor()
cursor.execute('create table filedata (id INTEGER PRIMARY KEY, filepath TEXT, filename TEXT, filesize INTEGER)')
d = DelayedSqlExecutor(cursor, paramtoken= '?') # using the ? paramtoken here for sqlite3. Leave it blank and it`ll use %s as support by Django etc.
d.addObject('filedata', ('id', 'filepath', 'filename', 'filesize'))
for i in range(0, 999):
# adding some dummy data. Notice the absence of the id-field. This will trigger inserts.
#Adding the id-field would trigger an update for data not yet in the db
d.addItem('filedata', {'filepath': '/tmp/', 'filename': 'test%s.txt' % i, 'filesize': i})
# No SQL has been executed yet, the default limit is 1000 items
# Adding another item will trigger the execution of SQLs and reset the d-instance
d.addItem('filedata', {'filepath': '/tmp/', 'filename': 'test%s.txt' % i, 'filesize': i})
# Adding some records to update
d.addItem('filedata', {'id': 1, 'filepath': '/tmp/', 'filename': 'testmore%s.txt' % i, 'filesize': 100})
# calling close will execute any remaining SQLs
d.close()
# you might be required to call commit on the cursor to commit the data. Depends on how you set up the cursor/connection.
Product's homepage
Requirements:
· Python
What's New in This Release: [ read full changelog ]
· Backwards compatibility with django 1.3.x. Thanks to John Spray for this one.
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